We used ADAM optimizer [1]} with learning rate of 0.0001, \(\beta 1\)  = 0.5 and \(\beta 2\)  = 0.999. We used learning rate scheduling for training. For image-to-image models, the learning rate was reduced to one-fifth and one-tenth after 40 and 80 epochs. The models were trained, in total, for 100 epochs. For image-to-pose model, the learning rate was reduced to half and one-tenth after 100 and 200 epochs respectively. The model was trained for 250 epochs. For all models, the model with best validation accuracy was used for testing.
